Backup and restore
Backup and restore is the practice of preserving copies of data or system state and using them to recover it after loss, damage, or failure.
PostgreSQL Mistakes and How to Avoid Them
A backup is an independently stored copy of data and required state that can be used to recover the original after loss or corruption.
- How it is used
- Protects PostgreSQL data from loss, corruption, and damaging changes through recoverable copies and planned recovery.
- How deep it goes
- Explains backup failure modes, storage placement, automation, restore drills, and PITR with continuous archiving rather than exhaustive command reference.
- Examples
- Uses mirrored disks and a standby, pg_dump after DROP TABLE, backups under PGDATA, and a test-environment restore drill.
- What you can do after
- Operate/configure automated, separately stored, PITR-capable PostgreSQL backups and validate them through full test restores.
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Think Like a CTO
A backup is a standby system, copy, or retained resource that can support restoration or continued operation after a failure.
- How it is used
- Supports service continuity after failure while also retaining records for compliance or testing and development.
- How deep it goes
- Develops scope, documentation, frequency, retention, archive security, and restore rehearsal as operational decisions rather than implementation-level commands.
- Examples
- Uses an undocumented ImageMagick dependency and delayed discovery of deleted client data to show why rebuild instructions and retention matter.
- What you can do after
- Practice/perform restore rehearsals and choose backup scope, storage, and retention against a defined recovery goal.
MongoDB 8.0 in Action, Third Edition
A backup is a stored copy of database data that can be used to recover from loss or corruption.
- How it is used
- Protects database continuity by recovering data after deletion, corruption, failure, or ransomware and preserving records needed for audits.
- How deep it goes
- Explains Atlas snapshot restoration, target replacement, M0 dump-based recovery, and CLI restore options; notes limitations without detailing a full backup schedule.
- Examples
- Uses an accidentally deleted customer collection, ransomware, and Atlas CLI commands for snapshot and point-in-time restores.
- What you can do after
- Operate/configure it by choosing an Atlas restore target and recovery point, running the appropriate restore, and testing the procedure.
Read how MongoDB 8.0 in Action, Third Edition explains backup and restore →
Google Anthos in Action
A backup is a stored copy of data or system state that can be used for recovery after loss or failure.
- How it is used
- Protects Anthos and Kubernetes cluster state and application data before upgrades and after loss or corruption.
- How deep it goes
- Distinguishes etcd configuration backups from persistent-volume backups and recommends practicing full restoration, without providing detailed restore commands.
- Examples
- Uses scheduled admin-cluster backups, on-demand pre-upgrade backups, etcd backup scripts, Velero, and practiced cluster restoration.
- What you can do after
- Operate a separated backup plan and validate recovery for admin clusters, user clusters, etcd, and application data.
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API Design Patterns
A backup is a preserved copy of data intended to support recovery or restoration of the original data.
- How it is used
- Supports recovery from accidental loss while preserving a consistent view of API data.
- How deep it goes
- Distinguishes snapshots from exports and gives operational fallbacks, but does not specify backup implementation or restore procedures.
- Examples
- Uses an export sequence where resources are created, deleted, and exported at different times, producing smeared data.
- What you can do after
- Evaluate export designs and choose snapshot or operational safeguards for preserving recoverable API data.
Django in Action
A database backup is a restorable copy of database contents and structure saved separately from the live database.
- How it is used
- Protects existing database data before destructive model changes and data migrations.
- How deep it goes
- Explains the need for backups through column deletion and irreversible data loss, but does not detail backup or restore commands.
- Examples
- Uses the Promoter model’s name-field replacement to illustrate why existing database rows need protection.
- What you can do after
- Apply it by preserving a restorable database copy before removing fields or moving stored content.
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
A backup is a stored copy of data intended for recovery after data loss or corruption.
- How it is used
- Uses stored copies and service recovery features to protect application data from loss, corruption, deletion, and disasters.
- How deep it goes
- Explains S3 synchronization, restoration, versioning, and storage choices, while outlining managed database recovery limits.
- Examples
- Demonstrates bucket creation, directory synchronization, recursive restoration, versioning, and scheduled instance-store backups.
- What you can do after
- Apply it via AWS CLI by creating an S3 bucket, synchronizing files, restoring directories, and enabling versioning.
Terraform in Depth: Infrastructure as Code with Terraform and OpenTofu
A state backup is a preserved copy of Terraform state that can be restored as a prior state snapshot.
- How it is used
- Safeguards Terraform state before direct changes and provides a recovery path for corruption or backend data loss.
- How deep it goes
- Walks through state pull and push, including file and stdin input plus lineage and serial checks; defers backend-specific configuration.
- Examples
- Uses a saved `my_backup.tfstate` file to demonstrate state pull, state push, stdin restoration, and forced restoration.
- What you can do after
- Practice/perform it: save and restore Terraform state snapshots, and test backend backups before an emergency.
Apache Kafka in Action
A backup is a separately retained copy of data that can be used to restore the original after loss or corruption.
- How it is used
- Guides decisions about whether Kafka data needs independent retention and how recovery fits into streaming-platform operations.
- How deep it goes
- Explains backup selection, snapshot timing risks, and operational dependencies, but stops short of a complete restoration procedure.
- Examples
- Uses database reimport, short-lived messages, filesystem snapshots, partition movement, and additional data centers as examples.
- What you can do after
- Evaluate whether Kafka needs backup, compare snapshots with mirroring, and identify supporting recovery controls.
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Architecting an Apache Iceberg Lakehouse
A backup is a separate copy of data retained so that the data can be restored after loss, corruption, or other failure.
- How it is used
- Protects lakehouse integrity by enabling restoration after storage, software, deletion, or regional failures.
- How deep it goes
- Explains layered automation and restoration steps, while deferring detailed Iceberg recovery mechanics to related operational guidance.
- Examples
- Uses metadata exports, catalog-state backups, replicated table paths, metadata.json restoration, and recovery DAGs as concrete artifacts.
- What you can do after
- Operate/configure it through automated backups, cross-region replication, restoration workflows, lineage validation, and monitoring triggers.
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Related concepts
- export methodcontrasts with · An export method is an interface element that makes data or functionality available to external consumers or systems.
- data lossaddresses · Data loss is the destruction, corruption, deletion, or unavailability of information that is expected to be retained or remain usable.
- snapshotuses · A snapshot is a fixed representation or copy of data or system state as it existed at a particular point in time.
- differential backupincludes · A differential backup contains data changed since the most recent full backup.
- full backupincludes · A full backup is a complete copy of all selected data or system state at a particular point in time.
- disaster recoveryused by · Disaster recovery is the planning and execution of processes and capabilities for restoring systems, data, and services after a disruptive event.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.